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Online Early Work Maximization Problem on Two Hierarchical Machines with Buffer or Rearrangements

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Algorithmic Aspects in Information and Management (AAIM 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13513))

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Abstract

In this paper, we consider two semi-online models of online early work maximization problem on two hierarchical machines. When a buffer size of K is available, we propose an optimal online algorithm with a competitive ratio of \(\frac{4}{3}\). If we are allowed to reassign at most K jobs after all the jobs have been scheduled, we propose an optimal online algorithm with a competitive ratio of \(\frac{4}{3}\).

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Acknowledgment

The work is supported in part by the National Natural Science Foundation of China [No. 12071417].

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Authors and Affiliations

  1. School of Mathematics and Statistics, Yunnan University, Kunming, 650504, People’s Republic of China

    Man Xiao, Xihua Bai & Weidong Li

Authors
  1. Man Xiao
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  2. Xihua Bai
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  3. Weidong Li
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Corresponding author

Correspondence to Weidong Li .

Editor information

Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Qiufen Ni

  2. University of Texas at Dallas, Richardson, TX, USA

    Weili Wu

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Xiao, M., Bai, X., Li, W. (2022). Online Early Work Maximization Problem on Two Hierarchical Machines with Buffer or Rearrangements. In: Ni, Q., Wu, W. (eds) Algorithmic Aspects in Information and Management. AAIM 2022. Lecture Notes in Computer Science, vol 13513. Springer, Cham. https://doi.org/10.1007/978-3-031-16081-3_5

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  • DOI: https://doi.org/10.1007/978-3-031-16081-3_5

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  • Print ISBN: 978-3-031-16080-6

  • Online ISBN: 978-3-031-16081-3

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